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Weather Risk Management in Agriculture

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Weather Risk Management in Agriculture ACTA UNIVERSITATIS AGRICULTURAE ET SILVICULTURAE MENDELIANAE BRUNENSIS Volume 64 146 Number 4, 2016 http://dx.doi.org/10.11118/actaun201664041303 WEATHER RISK MANAGEMENT IN AGRICULTURE Martina Bobriková1 1 Department of Finance, Faculty of Economics, Technical University of Košice, B. Nemcovej 32, 040 01 Košice, Slovak Republic. Abstract BOBRIKOVÁ MARTINA. 2016. Weather Risk Management in Agriculture. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, 64(4): 1303–1309. The paper focuses on valuation of a weather derivative with payoffs depending on temperature. We use historical data from the weather station in the Slovak town Košice to obtain unique prices of option contracts in an incomplete market. Numerical examples of prices of some contracts are presented, using the Burn analysis. We provide an example of how a weather contract can be designed to hedge the financial risk of a suboptimal temperature condition. The comparative comparison of the selected option hedging strategies has shown the best results for the producers in agricultural industries who hedges against an unfavourable weather conditions. The results of analysis proved that by buying put option or call option, the farmer establishes the highest payoff in the case of temperature decrease or increase. The Long Straddle Strategy is the most expensive but is available to the farmer who hedges against a high volatility in temperature movement. We conclude with the findings that weather derivatives could be useful tools to diminish the financial losses for agricultural industries highly dependent for temperature. Keywords: weather derivative, option contract, temperature, Burn analysis, hedging INTRODUCTION Ender and Zhang, 2015) analyze weather derivatives Weather often has a significant impact on as the potentially effective risk management tool for agricultural production. Climate change has agricultural industries. increased the frequency and intensity of catastrophic Like stated Alexandridis and Zapranis (2013) weather events that can caused serious financial weather derivatives can be used by corporations damages to the farmers (see, e.g., Černý et al., 2013; or individuals as part of risk management strategy Fukalová et al., 2014; Velecká et al., 2014). Actually, to reduce, i.e. hedge, risk associated with adverse it is to be expected that weather fluctuations will or unexpected weather conditions. They are increase in the future due to climate change (Pérez contracts with the payoff depending on the González and Yun, 2012). temperature, rainfall, snowfall, humidity, sunshine Weather and its changes have driven a demand or wind. Since, the most common underlying for weather risk management. Traditional insurance variable is temperature, temperature derivatives can be used to avoid high losses coming from will be considered in this paper. Weather market catastrophic events but it does not provide an is incomplete in the sense that the underlying adequate solution to mitigate financial losses which weather assets are not tradable. Therefore the price are caused by suboptimal weather conditions (Cyr of a weather derivative is usually based on various et al., 2010). Weather derivatives display advantages underlying weather indices. In the majority of over traditional insurances. The management of papers focused on weather derivatives, authors weather risk with derivatives is regular theme of deal with temperature indices Heating Degree Days scientific papers. For example studies (Chenet al., (HDD) index (for the fall and winter months) and 2011; Musshoffet al.; 2011; Spicka and Hnilica, 2013; Cooling Degree Days (CDD) index (the spring and 1303 1304 Ing. Martina Bobriková, Ph.D. summer months). There are for example works We also design hedging strategies, which can reduce (Considine, 2000; Taušer and Čajka, 2014). Jones economic impacts of temperature. (2011) examines the structure of HDD and CDD Pricing models for weather derivatives exist at contracts along with agricultural hedging uses of many levels of sophistication (see, e.g., Benth and weather derivatives. Benth, 2011; Benth and Benth, 2012; Schiller et al., Weather derivatives are usually structured as 2012; Zapranis and Alexandridis, 2009; Zapranis futures, swaps and option based on different and Alexandridis, 2011). The model shown here is underlying weather indices (see, e.g., Dischel, 2002). not necessarily what the market makers use. This In this work we will only study call/put weather said, a simple model can give a rough idea of what options. The buyer of a call option will receive a an option should cost. Our findings help to raise payoff if the underlying weather index value is the ability of them to understand the application of greater than the predetermined strike level at the weather derivatives in order to reduce the financial maturity day. The buyer of a put option will receive risk of suboptimal temperature events. Weather a payoff if the predetermined strike level is greater derivatives can be very useful to risk managers who than the underlying weather index value at the understand options and the risk profile associated maturity day. The buyer of a call/put option pays the with buying and selling weather options relative to seller a premium at the beginning of the contract. their business. When investors start to look at the Alaton et al. (2002) stated that a weather option can be weather derivatives market for hedging purposes, formulated by specifying the following parameters: increased liquidity as well as new products will contract type, contract period, weather station probably follow. from which the temperature data are obtained, underlying weather index, strike level. MATERIALS AND METHODS Weather options are either negotiated between two parties in the Over-The-Counter (OTC) market There is not a market for weather derivatives or traded on organized exchanges. The first exchange in Slovakia. This is attributed to the fact that it where standard weather derivatives could be traded is unclear whether and to what extent weather was the Chicago Mercantile Exchange (CME). derivatives are a useful instrument of risk Although the use of weather derivatives is now management. Since the most common underlying widespread and increasing, the European market variable is temperature, only the temperature based has not developed as quickly as the US market. The derivatives will be considered in this paper. A simple key fact is that their understanding by potential pricing formula for an option contract depending issuers and investors (primarily agricultural and on temperature index HDD will be suggested. energy industries) has been relatively poor. Agricultural application of weather derivatives to The main aim of this paper is to price and design risk management will be indicated. a weather derivative and to present the hedging The data were collected for the studied area Košice. strategies of a suboptimal weather. Based on the data Our methodology can be applied to different cities. set, we price the call/put options with the payoff The time period consists of 30 years (from 1984 to depending on temperature index HDD, using the 2013) with 10,958 observations. The data consists of Burn analysis. Basic source of data for the option daily minimum and maximum temperatures from pricing were daily average minimum and maximum the weather station in the mentioned area. Historical temperatures from the weather station in Košice. temperature observations were obtained from the National climatic data centre. In Fig. 1 is shown the daily average temperature in the studied area. 30 20 C ° 10 0 -10 emperature in emperature t -20 -30 1: Graph of the daily average temperature development in Košice from 1984 to 2013. (Source: The author’s processing based on historical temperatures from the National climatic data centre.) Weather Risk Management in Agriculture 1305 We use the burn analysis based on historical data The strike prices X calculated according to the from the studied area to compute the price of the papers (Garcia and Sturzenegger, 2001; Platen and option with payoff depending on temperature. The West, 2004; Roustant et al., 2003) have the following price of the option depends on the temperature forms: index and the strike price. Based on commonly used temperature index A : X = annual average HDD; HDD (heating degree-days index) presented by Zapranis and Alexandridis (2009), Benth and Benth (2011) and many others the options are priced. The daily value of the HDD index is: daily HDD (t) = max (18 - T (t), 0), where T(t) is the daily average temperature. The daily average temperature is calculated by averaging each day’s maximum and minimum temperature from midnight-to-midnight. To illustrate the RESULTS AND DISCUSSION concept of HDD, suppose that on a given winter day In pricing we consider following parameters: the high temperature was 11 degrees and the low • the risk-free interest rate is AAA-rated Slovakia temperature was 1 degree. This weather results in a government bond yield for 30 years maturity daily average temperature of 6 degrees with 12 HDD relating to the historical data, for this day. The lower is the temperature, the higher • the time of HDD option contract conclusion is 31st is the daily HDD. Weather options are written on of december 2013 and the contract is for annual the cumulative HDD over a specified period. The temperature events, annual payoff is calculated as: • 20% relation to the risk. anual payoff = annual average HDD × tick level. The partial results used in our analysis are in Tabs. I, II. All results can be provided upon request. The owner of a call option obtains the payoff if the HDD index value is higher than the strike price. Assuming the put option owner the payoff is paid if the strike price is higher than the HDD index value. Let us denote the annual average payoff µ, the standard deviation calculated from the annual payoffs σ, the risk-free interest rate r, the maturity date T, the relation to the risk α. The long and short option price is: long = e-rT (µ + α.σ), short = e-rT (µ − α.σ).
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